Single-cell immunology of SARS-CoV-2 infection.
Détails
ID Serval
serval:BIB_F4C681A1F5A5
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Synthèse (review): revue aussi complète que possible des connaissances sur un sujet, rédigée à partir de l'analyse exhaustive des travaux publiés.
Collection
Publications
Institution
Titre
Single-cell immunology of SARS-CoV-2 infection.
Périodique
Nature biotechnology
ISSN
1546-1696 (Electronic)
ISSN-L
1087-0156
Statut éditorial
Publié
Date de publication
01/2022
Peer-reviewed
Oui
Volume
40
Numéro
1
Pages
30-41
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
Publication Status: ppublish
Publication Status: ppublish
Résumé
Gaining a better understanding of the immune cell subsets and molecular factors associated with protective or pathological immunity against severe acute respiratory syndrome coronavirus (SARS-CoV)-2 could aid the development of vaccines and therapeutics for coronavirus disease 2019 (COVID-19). Single-cell technologies, such as flow cytometry, mass cytometry, single-cell transcriptomics and single-cell multi-omic profiling, offer considerable promise in dissecting the heterogeneity of immune responses among individual cells and uncovering the molecular mechanisms of COVID-19 pathogenesis. Single-cell immune-profiling studies reported to date have identified innate and adaptive immune cell subsets that correlate with COVID-19 disease severity, as well as immunological factors and pathways of potential relevance to the development of vaccines and treatments for COVID-19. For facilitation of integrative studies and meta-analyses into the immunology of SARS-CoV-2 infection, we provide standardized, download-ready versions of 21 published single-cell sequencing datasets (over 3.2 million cells in total) as well as an interactive visualization portal for data exploration.
Mots-clé
Animals, COVID-19/genetics, COVID-19/immunology, COVID-19/pathology, Data Analysis, Data Visualization, Datasets as Topic, Humans, Immunity, Innate, SARS-CoV-2/immunology, Single-Cell Analysis, Transcriptome
Pubmed
Web of science
Open Access
Oui
Création de la notice
04/01/2022 15:52
Dernière modification de la notice
06/05/2022 5:35